Among all of the methods in Table 1, the new model and BeatNet [1]} are joint beat and downbeat tracking approaches, and the rest are only beat tracking models. Also, except IBT [2]} and Aubio [3]}, all the other models are supervised, and they leverage deep neural networks to extract beat and/or downbeat activations.
Table 1 demonstrates that the proposed model can deliver the same beat tracking F-measure performance as the BeatNet [1]}, which is the state-of-the-art online approach. However, its downbeat performance is moderately lower than that of the BeatNet. The primary point is that using the proposed 1D state space and the jump-back reward technique leads to a more than 30x speedup than BeatNet, making it much more suitable for large scale industrial usages.
